Scienaptic - Data Science Role - Marketing Analytics

Data Science - Marketing Analytics

Data Scientist with 4 - 5 Years of Hands-On Experience

About the Role:

We are searching for a strategic and inquisitive Data Scientist to Develop and run with Data- Centred Projects. The chosen Candidate will be responsible for Developing all aspects of Data mining, Predictive Analytics, Solution Development to name a few.

Responsibilities:

- Work with Clients to understand Business Problems, Industry Context, Data Sources, Potential Risks and Constraints & execute the Projects/Tasks Independently.

- Translate the Business Program into a solvable Data Science Problem, propose different approaches and their Pros and Cons.

- Identify, Analyse and Interpret Trends or Patterns in Complex Data Sets.

- Build Market Mix Models (MMM), Multi-Touch Attribution Models (MTA), Optimize Marketing Spend and Come Up with Implementable Recommendations and Strategy/Plan.

- Good Written, Verbal, and Presentation Skills with the ability to generate and present meaningful Insights.

Requirements:

- 4-5 Years of Professional Experience in Advanced Data Science focused on, Econometric Modeling, Marketing Analytics, Market Mix modelling, Multi-touch Attribution, Micro Segment Attribution, Unified Measurement, Marketing Budget Optimization, TV Attribution etc.

- Ability to Analyse Complex Data and provide Recommendations to Business.

- Proficient with Statistical Analysis, AI/ML Algorithms & applying them on Large Datasets.

- Establish Scalable, Efficient Solutions for large scale Data Analysis, AI/ML Model Development, AI/ML Model Validation, AI/ML Model Implementation and AI/ML Model Automation (MLOps).

- Excellent proficiency in Core Python Fundamentals, Python Programming, and other relevant Python Frameworks (such as Django, Flask etc.), Object Relational Mapper Libraries, Pyspark, Scala & SQL.

- Strong Knowledge in AI/ML/DL Techniques, Algorithms, and Tools with exposure to OLS Regression/Multiple Linear Regression, Classification (Logistic Regression, Random Forest, XGBoost), Linear Attribution model, Time Decay Attribution, BG/NBD, Markov Chain, Shapley Additive Explanations, CNN, RNN (LSTM), Transformers (BERT) etc.

- Proficiency in working with Open-Source Deep Learning libraries like TensorFlow, Keras, Pytorch.

- Demonstrated ability to work Independently.

- Proven ability to Visualize Data for Influencing.

- Comfortable with Cloud-Based Platforms (AWS, Azure, Google).

- Experience in Digital Marketing (Web & App) is a must.

- Experience with Google Analytics, Adobe Analytics etc. is a plus.

- Proficient in communicating Technical findings to Non-Technical Stakeholders.

- Communicate Complex Data or Algorithms into simple Conclusions that will empower

- Leadership to drive action based on the Insights derived.

- Strong Presentation and Communication Skills.

- Data Scientist

Education: Bachelor's / Master's Degree in Engineering or any Quantitative discipline from a Premier Institute